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MultiFrailty: Shared Frailty Regression Models with Inverse Gaussian, Generalized Lindley, and Gamma Frailty Distributions

Implements shared frailty regression models for survival data under eight censoring mechanisms: exact, right censoring (Kalbfleisch and Prentice, 2002), left censoring, interval censoring (Sun, 2006), progressive Type I censoring, and progressive Type II censoring (Balakrishnan and Aggarwala, 2000 <doi:10.1007/978-1-4612-1334-5>). Combines four frailty distributions – Gamma (Clayton, 1978), Inverse Gaussian (Hougaard, 1984), and two variants of the Generalized Lindley (GL) distribution: GL Type 1, a two-component gamma mixture with distribution-specific scale/shape linkage (Pandey, Hanagal, and Tyagi, 2022), and GL Type 2, a two-component gamma mixture with a common rate parameter (Pandey and Tyagi, 2021 <doi:10.1134/S1995080222010140>) – with two baseline hazard distributions: the two-parameter Weibull distribution (Weibull, 1951) and the three-parameter Generalized (Exponentiated) Weibull distribution (Mudholkar and Srivastava, 1993 <doi:10.1109/24.229504>). A no-frailty baseline-only model is also supported for nested model comparison. Maximum likelihood estimation is conducted using Newton-Raphson and Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithms via the 'maxLik' package (Henningsen and Toomet, 2011 <doi:10.1007/s00180-010-0217-1>). Provides standard errors, confidence intervals, hypothesis tests, Akaike Information Criterion (AIC, Akaike, 1974 <doi:10.1109/TAC.1974.1100705>), Bayesian Information Criterion (BIC, Schwarz, 1978 <doi:10.1214/aos/1176344136>), corrected Akaike Information Criterion (AICc, Hurvich and Tsai, 1989), Hannan-Quinn Information Criterion (HQIC, Hannan and Quinn, 1979), a bootstrap approximation of the Widely Applicable Information Criterion (WAIC, Watanabe, 2010), k-fold cross-validation, frailty variance estimation, survival, hazard, median, risk, and marginal predictions, Cox-Snell (Cox and Snell, 1968), martingale (Barlow and Prentice, 1988), and deviance residuals with a Kolmogorov-Smirnov goodness-of-fit test, influence diagnostics (leverage, Cook's distance, difference in fits (DFFITS), difference in betas (DFBETAS); Belsley, Kuh, and Welsch, 1980), random data generation under all eight censoring mechanisms, a Monte Carlo simulation-study function, and a diagnostic and survival plotting suite.

Version: 0.1.0
Depends: R (≥ 4.0.0)
Imports: survival, maxLik, numDeriv, stats, graphics, grDevices, utils
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown
Published: 2026-08-07
DOI: 10.32614/CRAN.package.MultiFrailty (may not be active yet)
Author: Shikhar Tyagi ORCID iD [aut, cre], Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi at gmail.com>
License: GPL-3
NeedsCompilation: no
Language: en-US
Citation: MultiFrailty citation info
Materials: README
CRAN checks: MultiFrailty results

Documentation:

Reference manual: MultiFrailty.html , MultiFrailty.pdf
Vignettes: Introduction to MultiFrailty: Shared Frailty Regression Models (source, R code)
Reproducing Source Papers with MultiFrailty (source, R code)

Downloads:

Package source: MultiFrailty_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): MultiFrailty_0.1.0.tgz, r-oldrel (arm64): MultiFrailty_0.1.0.tgz, r-release (x86_64): MultiFrailty_0.1.0.tgz, r-oldrel (x86_64): MultiFrailty_0.1.0.tgz

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.